This paper discusses key concepts in the emerging field of technology-mediated task-based language teaching (TMTBLT) and provides a research agenda for moving this sub-field forward in a theoretically sound and data-driven way. We first define TMTBLT and discuss the importance of considering technological affordances and specific learning contexts…

The purpose of this paper is to present a specific case of CALL task design adopting the patterns-based learning design approach. The approach provides a common framework/vocabulary for educational designers, particularly teachers, to systematically capture, articulate, make explicit, share and reuse expert knowledge of teaching and good design.…

Purpose: The paper aims to present a new two stage local causal learning algorithm -- HEISA. In the first stage, the algorithm discoveries the subset of features that better explains a target variable. During the second stage, computes the causal effect, using partial correlation, of each feature of the selected subset. Using this new algorithm,…

This book presents how Digital Transformation is a requirement to upgrade Latin American universities to a next level in management, lecturing and learning processes and strategies. The book starts with a thorough introduction of the Latin American context addressing the three main topics in the book: Digital Transformation, Higher Education and…

Using a corpora approach involves using a series of texts in the language under study as a type of corpus on which to base acquisition. Languages in all forms (written, spoken, performed, formal, informal, etc.) are captured all the time through online and digital platforms, apps, etc. making them highly accessible. Applying corpora in teaching…

Aim/Purpose: This study aims to explore the innovative integration of machine learning techniques into project-based learning rooted in Malay ethnoscience in Jambi, Indonesia. The research introduces a novel framework that utilizes educational data mining to personalize culturally responsive STEM education in under-resourced public schools.…

In our age of big data and growing computational power, versatility in data analysis is important. This study presents a flexible way to combine statistics and machine learning for data analysis of a large-scale educational survey. The authors used statistical and machine learning methods to explore German students' attitudes towards information…

In this theoretical paper, we argue that Tech enthusiasts and skeptics are animated by the same sociotechnical personalization imaginary to improve education and teaching through personalization, but see very different paths to this goal. Tech boosters point to well-known problems of the existing education system -- and rhetorically ask: 'why…

Over the last decade, there has been great research interest in the application of artificial intelligence (AI) in various fields, such as medicine, finance, and law. Recently, there has been a research focus on the application of AI in education, where it has great potential. Therefore, a systematic review of the literature on AI in education is…

Online educational games have been widely used to support students' mathematics learning. However, their effects largely depend on student-related factors, the most prominent being their behavioral characteristics as they play the games. In this study, we applied a set of learning analytics methods (k-means clustering, data visualization) to…

This research was triggered by the identified need in literature for large-scale studies about the kinds of designs that teachers create for mobile learning (m-learning). These studies require analyses of large datasets of learning designs. The common approach followed by researchers when analyzing designs has been to manually classify them…

Online educational games have been widely used to support students' mathematics learning. However, their effects largely depend on student-related factors, the most prominent being their behavioral characteristics as they play the games. In this study, we applied a set of learning analytics methods ("k"-means clustering, data…

Providing high-level support to students on NGSS inquiry practices can be challenging; however, teacher dashboards can help teachers provide just-in-time instruction to students, both in-person and online. Prior work has shown some success with a dashboard that alerts teachers in real time on students' science inquiry difficulties, but teachers…

Machine learning methods for predictive analytics have great potential for uncovering trends in educational data. However, simple linear models still appear to be most widely used, in part, because of their interpretability. This study aims to address the issues of interpretability of complex machine learning classifiers by conducting feature…

The aim of this study was to examine the relationship between common classroom help-seeking determinants (achievement goals, self-efficacy, prior knowledge, gender, and help-seeking perceptions) and help-seeking behaviors online (hint use percentage, latency of help seeking, answer attempt percentage, feedback level percentage, and seeking help…